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Johnson & Johnson
Johnson & Johnson
H1B vīzas sponsorsFarmaceitiskie produktiVeselības apdrošināšanaVeselības aprūpe
Johnson & Johnson ir globāls veselības aprūpes uzņēmums, kas darbojas inovatīvu zāļu un medicīnas tehnoloģiju jomā. Tā komandas izstrādā risinājumus onkoloģijā, imunoloģijā, neirozinātnē, specializētajā oftalmoloģijā, invazīvajā aprūpē un ortopēdijā, apvienojot zinātni un tehnoloģijas, lai risinātu sarežģītas veselības aprūpes vajadzības. Uzņēmums pievēršas arī veselības vienlīdzībai, vides ilgtspējai, daudzveidībai un iekļaušanai, apkalpojot veselības aprūpes sniedzējus, pacientus un kopienas visā pasaulē.
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Vakances uzņēmumā

Director of Research Data Foundation

Lead FAIR data platforms and governance for Johnson & Johnson’s Innovative Medicines R&D. Make research data trusted and reusable for discovery, analytics, AI, and scientific decisions.

USAmerikas Savienotās ValstisNJŅūdžersijaPAPensilvānijaHibrīdiPilna slodzeVadošais speciālistsNepieciešamā Valoda: angļuDirektors
KiberdrošībaMākonis

Apraksts

  • Lead technology capabilities that make research data trusted, governed, and reusable across the Research organization.
  • Transform data from fragmented systems, instruments, labs, and scientific workflows into a FAIR environment.
  • Work with research functions, lab informatics teams, data product owners, scientists, data science and modeling teams, governance leaders, architects, cybersecurity specialists, and technology platform teams.
  • Turn research strategy, FAIR principles, scientific data needs, and AI-readiness requirements into scalable platforms, metadata practices, data services, standards, scorecards, and operating routines.
  • Lead scalable data ingestion and curation platforms, covering onboarding, metadata enrichment, pipeline engineering, orchestration, monitoring, and issue resolution.
  • Enable consistent naming, identifiers, provenance, lineage, ontologies, vocabularies, quality thresholds, stewardship, sharing, and compliant scientific reuse.
  • Provide governed, high-performance access to distributed R&D data through integration and data virtualization.
  • Define and run research data quality and FAIR frameworks, standards, thresholds, and executive reporting.
  • Set quality rules, ownership, metadata expectations, FAIR acceptance criteria, and automated governance monitoring.
  • Use quality and FAIR insights to set remediation priorities and measurable improvement roadmaps.
  • Lead research data catalog, metadata, ontology, lineage, and master and reference data capabilities.
  • Establish canonical research entities, identifiers, controlled vocabularies, semantic standards, metadata, lineage, and provenance across research platforms and workflows.
  • Enable consistent data semantics across compounds, targets, assays, samples, studies, experiments, instruments, and other scientific domains.

Prasības

  • Master’s degree or equivalent experience in computer science or life sciences.
  • At least 10 years of progressive technology leadership experience in a relevant area.
  • Experience in research data platform engineering, scientific data architecture, laboratory informatics, or enterprise research data management.
  • Experience designing and implementing cloud-based FAIR data environments, semantic and metadata capabilities, and enterprise master and reference data solutions.
  • Understanding of FAIR data principles, data product management, data contracts, research governance workflows, privacy, security, compliance, AI-ready data, and platform operating models.
  • Demonstrated success leading cross-functional teams and influencing research leaders and scientists.
  • Excellent communication skills and the ability to turn complex data platform and governance topics into clear business decisions and outcomes.
  • A record of building and operating enterprise-grade data solutions.
  • Experience establishing operating models for governed, reusable data assets.
  • Ability to work with scientists, data science, analytics, business, and technology organizations.
  • Experience managing critical data services with reliability targets, operational metrics, issue remediation, cost optimization, and service improvement routines.
  • A record of driving adoption of shared platforms, common standards, self-service patterns, metadata practices, governance workflows, and data product lifecycle management.
  • Strong executive influencing skills.

Priekšrocības

  • Inclusive work environment.
  • Equal opportunity employment.
  • Inclusive interview process.
  • Disability accommodations during the interview process.

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